CN110275119A - A kind of cell health state assessment models construction method, appraisal procedure and device - Google Patents
A kind of cell health state assessment models construction method, appraisal procedure and device Download PDFInfo
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- CN110275119A CN110275119A CN201910707591.9A CN201910707591A CN110275119A CN 110275119 A CN110275119 A CN 110275119A CN 201910707591 A CN201910707591 A CN 201910707591A CN 110275119 A CN110275119 A CN 110275119A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
Abstract
The present invention relates to a kind of cell health state assessment models construction method, appraisal procedure and devices, obtain the theoretical operating parameter collection of battery；Based on theoretical operating parameter collection, the theoretical life model of each default type battery is established；Obtain actual operation parameters collection of each default type battery under default influence factor effect；The theoretical life model of each default type battery is modified respectively, obtain each of the lower cell health state assessment models for presetting type battery of default influence factor effect, so that after the characteristic of battery to be assessed to be input to the cell health state assessment models of corresponding default type battery, obtain the health status of the battery to be assessed of output, realize the degradation not needed to electrode material, diaphragm state, voltage, the content of lithium ion measures in internal resistance and electrolyte, online evaluation only can be carried out to the health status of battery by the cycle-index of mesuring battary, and place to use is unrestricted, practicability is higher.
Description
Technical field
The present invention relates to used batteries prediction technical fields, and in particular to a kind of cell health state assessment models
Construction method, appraisal procedure and device.
Background technique
In recent years, new-energy automobile industry is risen and fast-developing, with the popularization in market and the raising of user cognition degree,
In the coming years, explosive growth will occur for the ownership of new-energy automobile.As the dynamical system of automobile, power battery
Health status becomes the most concerned problem of car owner.The factor for influencing power battery health status is more, such as power battery itself property
Can influence, influence, influence of driver's battery use habit of environment etc. in use process.
In the prior art, multi-pass crosses the parameters such as internal resistance, capacity, charge-discharge magnification and cycle-index and carries out cell health state
Assessment, common estimation method are physics off-line test method.Physics off-line test method mainly under conditions of one stable, is incited somebody to action
Power battery is placed in the test program of a setting, carries out Physical Experiment to power battery, to the degradation of electrode material,
The content of lithium ion measures in diaphragm state, voltage, internal resistance and electrolyte, to realize to power battery health status
Offline estimation.
But this assessment mode only just may be implemented to be good for power battery in the state that electric car is out of service
The assessment of health state, can not real-time online obtain battery health status, place to use is made practicability not by biggish limitation
It is high.
Summary of the invention
In view of this, the purpose of the present invention is to provide a kind of cell health state assessment models construction methods, assessment side
Method and device, with overcome at present can not real-time online obtain the health status of battery, place to use is practical by biggish limitation
The not high problem of property.
In order to achieve the above object, the present invention adopts the following technical scheme:
A kind of cell health state assessment models construction method, comprising:
Obtain the theoretical operating parameter collection of each default type battery；
Based on the theoretical operating parameter collection, the theoretical life model of each default type battery is established；
Obtain actual operation parameters collection of each default type battery under default influence factor effect；
Based on the actual operation parameters collection, respectively to the theoretical life model of each default type battery into
Row amendment, the cell health state for obtaining each of the lower default type battery of the default influence factor effect assess mould
Type, so as to which the cell health state that the characteristic of battery to be assessed is input to the corresponding default type battery is assessed mould
After type, the health status of the battery to be assessed of output is obtained.
Further, above-described a kind of cell health state assessment models construction method, the theory operating parameter
Collection includes that all unit cells in each default type battery recycle corresponding theoretical health status collection every time；
It is described to be based on the theoretical operating parameter collection, establish the theoretical life model of each default type battery, comprising:
According to the theoretical health status collection, the parameter Estimation vector of each default type battery is determined；
According to the parameter Estimation vector, the theoretical life model of each default type battery is determined.
Further, above-described a kind of cell health state assessment models construction method, the actual operation parameters
Collection includes that all unit cells in each default type battery recycle corresponding practical health status collection every time；
It is described to be based on the actual operation parameters collection, respectively to the theoretical service life mould of each default type battery
Type is modified, and the cell health state for obtaining each of the lower default type battery of the default influence factor effect is assessed
Model, comprising:
According to the theoretical health status collection, the corresponding theoretical parameter vector set of each default type battery is determined；
Based on the theoretical parameter vector set, the priori point of the actual parameter vector of each default type battery is determined
Cloth；
According to the theoretical life model, the likelihood of the actual parameter vector of each default type battery is determined
Function；
Based on the likelihood function and the prior distribution, the actual parameter of each default type battery is determined
The Posterior distrbutionp of vector；
Obtain corresponding estimation function at the Posterior distrbutionp maximum value；
Based on the Posterior distrbutionp, the estimation function and the practical health status collection, preset iterative instruction is executed,
Obtain the target component vector of each default type battery；
According to the target component vector, the cell health state assessment mould of revised each default type battery is determined
Type.
Further, above-described a kind of cell health state assessment models construction method, it is described to be based on the posteriority
Distribution, the estimation function and the practical health status collection, execute preset iterative instruction, obtain each default type
The target component vector of battery, comprising:
The current state parameter for extracting each default type battery, the current state are concentrated from practical health status
Parameter includes currently practical cell health state and the corresponding current cycle time of the currently practical cell health state；
The current state parameter is substituted into corresponding current Posterior distrbutionp, next priori when being corrected next time
Distribution, and, the current state parameter is substituted into corresponding current estimation function, obtain it is described when correcting next time under
One parameter Estimation vector；
According to next prior distribution and next parameter Estimation vector, using Bayes' theorem, determine it is described under
Next Posterior distrbutionp when primary amendment；
The target component estimate vector in each default type battery last time iteration is obtained as the target
Parameter vector.
Further, above-described a kind of cell health state assessment models construction method, it is described according to the theory
Health status collection determines the corresponding theoretical parameter vector set of each default type battery, comprising:
Respectively to the theoretical health status concentrate the corresponding health status of circulation every time of each unit cells into
Row fitting, obtains the theoretical fitting function of each unit cells in each default type battery；
The coefficient of each theoretical fitting function is respectively combined as theoretical parameter vector；
All theoretical parameter vectors of each default type battery are formed into each default type battery
The theoretical parameter vector set.
Further, above-described a kind of cell health state assessment models construction method, it is described to obtain described preset
Each of under influence factor effect after the cell health state assessment models of the default type battery, further includes:
All cell health state assessment models are stored into preset cell health state assessment models library.
The present invention also provides a kind of cell health state appraisal procedures, comprising:
Obtain the characteristic of battery to be assessed；The characteristic include the battery to be assessed type, influence because
Element and current cycle time；
From all cell health state assessment models pre-established, the determining and described battery variety to be assessed, influence
The target battery health state evaluation model that factor is consistent；The cell health state assessment models pass through described in any of the above item
Cell health state assessment models construction method building；
Based on the current cycle time and target battery health state evaluation model, the strong of the battery to be assessed is determined
Health state.
The present invention also provides a kind of cell health state assessment models construction devices, comprising: first obtains module, establishes
Module and correction module；
Described first obtains module, for obtaining the theoretical operating parameter collection of each default type battery；
It is described to establish module, for establishing the reason of each default type battery based on the theoretical operating parameter collection
By life model；
Described first obtains module, is also used to obtain each default type battery under the effect of default influence factor
Actual operation parameters collection；
The correction module, for being based on the actual operation parameters collection, respectively to each default type battery
The theory life model is modified, and each of obtains under the default influence factor effect electricity of the default type battery
Pond health state evaluation model, so as to which the characteristic of battery to be assessed to be input to the electricity of the corresponding default type battery
After the health state evaluation model of pond, the health status of the battery to be assessed of output is obtained.
Further, above-described a kind of cell health state assessment models construction device, the theory operating parameter
Collection includes that all unit cells in each default type battery recycle corresponding theoretical health status collection every time；
It is described to establish module, it is also used to determine each default type battery according to the theoretical health status collection
Parameter Estimation vector；According to the parameter Estimation vector, the theoretical life model of each default type battery is determined.
The present invention also provides a kind of cell health states to assess device, comprising: second obtains module and determining module；
Described second obtains module, for obtaining the characteristic of battery to be assessed；The characteristic include it is described to
Assess type, influence factor and the current cycle time of battery；
The determining module, for from all cell health state assessment models pre-established, it is determining with it is described to
The target battery health state evaluation model that assessment battery variety, influence factor are consistent；The cell health state assessment models
It is constructed by cell health state assessment models construction method described in any one of claims 1-6；
The determining module is also used to based on the current cycle time and target battery health state evaluation model, really
The health status of the fixed battery to be assessed.
A kind of cell health state assessment models construction method, appraisal procedure and device of the invention, using the above technology
Scheme, by the theoretical operating parameter collection for obtaining battery；Based on theoretical operating parameter collection, the reason of each default type battery is established
By life model；Obtain actual operation parameters collection of each default type battery under default influence factor effect；Based on reality
Operating parameter collection is respectively modified the theoretical life model of each default type battery, obtains default influence factor effect
Under each of default type battery cell health state assessment models, so as to which the characteristic of battery to be assessed is input to pair
After the cell health state assessment models for the default type battery answered, the health status of the battery to be assessed of output is obtained, is realized
Do not need that the degradation to electrode material, diaphragm state, voltage, the content of lithium ion is surveyed in internal resistance and electrolyte
Amount only can carry out online evaluation by the cycle-index of mesuring battary to the health status of battery, and place to use not by
Limitation, can be with real-time detection, and practicability is higher.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Fig. 1 is a kind of flow chart of cell health state assessment models construction method embodiment one of the invention；
Fig. 2 is a kind of flow chart of cell health state assessment models construction method embodiment two of the invention；
Fig. 3 is a kind of schematic diagram of cell health state assessment models of the invention under dual factors effect；
Fig. 4 is a kind of flow chart of cell health state appraisal procedure embodiment of the invention；
Fig. 5 is a kind of structure chart of cell health state assessment models construction device embodiment one of the invention；
Fig. 6 is a kind of structure chart of cell health state assessment models construction device embodiment two of the invention；
Fig. 7 is a kind of structure chart of cell health state assessment Installation practice of the invention.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, technical solution of the present invention will be carried out below
Detailed description.Obviously, described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Base
Embodiment in the present invention, those of ordinary skill in the art are obtained all without making creative work
Other embodiment belongs to the range that the present invention is protected.
Fig. 1 is a kind of flow chart of cell health state assessment models construction method embodiment one of the invention.Such as Fig. 1 institute
Show, the cell health state assessment models construction method of the present embodiment can specifically include following steps:
S101, the theoretical operating parameter collection for obtaining each default type battery；
When being directed to cell performance evaluation both at home and abroad at present, common technical indicator is remaining battery service life
(Remaining Useful Life, RUL) also is understood as cell health state (State Of Health, SOH) assessment,
What SOH was characterized is the health status of battery, is defined as battery under certain working environment, actual capacity and the specified appearance of new battery
The ratio between amount thinks making for battery when the actual capacity of battery is reduced to the 80% of rated capacity when that is, the SOH value of battery is 0.8
It has been terminated with the service life.In the present embodiment, by assessing SOH, with the health status of determination battery to be assessed.
The present embodiment from battery attributes feature, using material properties, process attribute and other attributes (including brand,
Cell degradation degree etc.) specifically classified to battery, obtain the battery of different default types.Pass through the public data of network
The theoretical operating parameter collection of each default type battery is established in (such as vehicle net), use environment data and Physical Experiment.Wherein
Theoretical operating parameter collection includes that all unit cells in each default type battery recycle corresponding theoretical health status every time
Composed theory health status collection.
S102, it is based on theoretical operating parameter collection, establishes the theoretical life model of each default type battery；
In the present embodiment, each default type battery can be established according to the theoretical operating parameter collection obtained in advance respectively
Theoretical life model.
S103, actual operation parameters collection of each default type battery under default influence factor effect is obtained；
Each battery sensor for presetting type battery collected data under the default influence factor effect of difference are obtained,
Using these data as actual operation parameters collection.
Wherein, actual operation parameters collection may include that all unit cells in each default type battery recycle pair every time
Practical health status collection composed by the practical health status answered.
S104, it is based on actual operation parameters collection, the theoretical life model of each default type battery is modified respectively.
It, can be according to the parameter that actual operation parameters are concentrated to each after obtaining actual operation parameters collection in the present embodiment
The theoretical life model of default type battery is modified, each of under the as default influence factor effect of the model after correcting
The cell health state assessment models of default type battery, so as to the characteristic of battery to be assessed is input to corresponding default
After the cell health state assessment models of type battery, the health status of the battery to be assessed of output is obtained.
The cell health state assessment models construction method of the present embodiment, by the theoretical operating parameter collection for obtaining battery；
Based on theoretical operating parameter collection, the theoretical life model of each default type battery is established；Each default type battery is obtained to exist
Actual operation parameters collection under default influence factor effect；Based on actual operation parameters collection, respectively to each default type battery
Theoretical life model be modified, obtain each of the lower cell health state for presetting type battery of default influence factor effect
Assessment models, so as to which the cell health state that the characteristic of battery to be assessed is input to corresponding default type battery is assessed
After model, the health status of the battery to be assessed of output is obtained, realizes and does not need the degradation to electrode material, septiform
The content of lithium ion measures in state, voltage, internal resistance and electrolyte, only can be to battery by the cycle-index of mesuring battary
Health status carry out online evaluation, and place to use is unrestricted, can be with real-time detection, practicability is higher.
Fig. 2 is a kind of flow chart of cell health state assessment models construction method embodiment two of the invention.Such as Fig. 2 institute
Show, the cell health state assessment models construction method of the present embodiment can specifically include following steps:
S201, the theoretical operating parameter collection for obtaining each default type battery；
Specifically, this step is identical as the implementation procedure of the S101 of Fig. 1 embodiment, and details are not described herein again.
S202, according to theoretical health status collection, determine the parameter Estimation vector of each default type battery；
Those skilled in the art can recycle correspondence according to all unit cells in each default type battery every time
Theoretical health status collection and previous experience, estimate the parameter Estimation vector of each default type battery.
Specifically, unknown parameter coefficient is provided in function, there may be multiple coefficients for a function, combine multiple coefficients
It is together parameter vector.
S203, according to parameter Estimation vector, determine the theoretical life model of each default type battery；
In the present embodiment, according to the parameter Estimation vector that estimation obtains, the theoretical service life of each type battery can be determined
Model are as follows: y=(a, x)+ε, ε~N (0, σ1 2)。
X is cycle-index, and y is the corresponding cell health state of cycle-index, and a is parameter Estimation vector, and ε is random perturbation
, σ1 2For the variance of ε, N indicates Disturbance ε Normal Distribution herein.It is possible to further, it is evident that the theoretical longevity
Life model is the functional relation of y (cell health state) about x (cycle-index), and wherein a (parameter Estimation vector) is unknown
The parameter Estimation vector of number x.
S204, actual operation parameters collection of each default type battery under default influence factor effect is obtained；
Obtain actual operation parameters collection of each default type battery under default influence factor effect.Wherein, practical fortune
Row parameter set may include that all unit cells in each default type battery recycle corresponding practical health status collection every time.
Further, presetting influence factor is the factor that can be had an impact to the health status of battery.In the present embodiment,
Default influence factor may include battery attributes, battery management system (Battery Management System, BMS), battery
Five use environment, charge-discharge characteristics and driving behavior (driving behavior for pertaining only to influence battery performance) major class, specifically
39 sub- indexs as shown in 1 cell health state System of Comprehensive Evaluation of table can be divided into.
Table 1
In the process of running, the service life is not often only to be influenced by a kind of factor, but be total to by many factors to battery
With influence, therefore the present invention also considers influence of the reciprocation to battery life between multifactor simultaneously, therefore, in the present embodiment,
Default influence factor does not only include the single influence factor in table 1, further includes the collective effect of many factors.For example, fast charge+
80% discharge capacity, low temperature+trickle charge+80% discharge capacity, high speed+room temperature+average daily mileage 0km-20km+ high initiation culture etc.
Deng.Since individual Multifactor Combinations under theoretical condition are difficult to realize for small probability event under real world conditions, therefore need to
Multifactor conditional combination is screened, small probability event is rejected.
Wherein, the content difference that the present embodiment provides that each factor is included is as follows:
Vehicle manufacturers: Vehicle manufacturers A, Vehicle manufacturers B, Vehicle manufacturers C etc.；
Vehicle model: vehicle model is produced the concrete model of vehicle by each production firm；
Category of roads: high speed, 1 grade, 2 grades, 3 grades, 4 grades of highways；
Congestion level: unimpeded, substantially unimpeded, slight congestion, moderate congestion, heavy congestion；
Temperature: low temperature, room temperature, high temperature；
Road surface safety: it is absolutely unsafe, is more dangerous, is general, is safer, safety；
Fast charge: fast charge, trickle charge；
It is fully charged: often, sometimes, never；
Rate of charge: 0.5C, 0.8C, 1C, 1.2C, 1.5C；
Discharge-rate: high and low；
Over-discharge: often, sometimes, never；
Depth of charge: 50-SOC, 50-80SOC, 80+SOC；
Depth of discharge: 30-SOC, 30-50SOC, 50-70SOC, 70+SOC；
Charge and discharge are accustomed to: shallowly filling and shallowly put, fill deeply and put deeply, shallowly fill and put deeply, fill and shallowly put deeply；
It is anxious to accelerate: often, sometimes, never；
Other loads are opened: often, sometimes, never；
Total kilometrage: 10,000 km-4, ten thousand km, 40,000 km-8, ten thousand km, 80,000 km-12, ten thousand km, 120,000 km-16, ten thousand km, 160,000 km-20 ten thousand
km；
Average daily mileage: 0km-20km, 20km-40km, 40km-60km, 60km-80km, 80km-100km；
Initiation culture: high, medium and low；
Charge and discharge cycles number: 50-100 times, 100-150 times, 150-200 times, 200-250 times, 250-300 times, 300-
350 times, 350-400 times, 400-450 times, 450-500 times, 500-550 times, 550-600 times；
Charge volume mode: 25-35SOC, 35-45SOC, 45-55SOC, 55-65SOC, 65-75SOC, 75-85SOC, 85-
95SOC,95-100SOC；
Discharge capacity mode: 0-10SOC, 10-20SOC, 20-30SOC, 30-40SOC, 40-50SOC, 50-60SOC, 60-
70SOC,70-80SOC；
Temperature equalization: with and without this function；
Active and passive equilibrium: active equalization, passive equilibrium.
S205, the corresponding health status of circulation every time of each unit cells is concentrated to intend theoretical health status respectively
It closes, obtains the theoretical fitting function of each unit cells in each default type battery；
In the present embodiment, each unit cells that can be concentrated respectively to theoretical health status recycle corresponding health every time
State is fitted, and is obtained in all default type batteries, the theoretical fitting function of each unit cells.
S206, the coefficient of each theoretical fitting function is respectively combined as theoretical parameter vector；
It in the present embodiment, obtains in all default type batteries after the theoretical fitting function of each unit cells, obtains every
The coefficient sets of each theoretical fitting function are combined into a theoretical parameter vector respectively by the coefficient of a theoretical fitting function.
S207, each the theoretical of default type battery of all theoretical parameter vectors composition of each default type battery is joined
Number vector collection；
All theoretical parameter vectors of each default type battery are combined, the theoretical ginseng of each default type battery is formed
Number vector collection.
S208, it is based on theoretical parameter vector set, determines the prior distribution of each default type battery actual parameter vector；
In the present embodiment, each default type battery actual parameter vector can be determined according to theoretical parameter vector set
Prior distribution are as follows:
P1(ω)=N (ω | W, Σ)
Wherein, P1For prior probability；ω is actual parameter vector；ω | W is the mean value of theoretical parameter vector set；Σ is reason
By the covariance matrix of parameter vector collection；N indicates ω Normal Distribution.
It is possible to further, it is evident that prior distribution is P1The letter of (prior probability) about ω (actual parameter vector)
Number relational expression.
S209, according to theoretical life model, determine the likelihood function of the actual parameter vector of each default type battery；
Specifically, the actual parameter vector of each default type battery can also be determined respectively according to theoretical life model
Likelihood function are as follows:
P2(y | ω)=N (y | y (a, x), σ2 2)
Wherein, P2For likelihood probability, ω is actual parameter vector, and y (a, x) is theoretical life model, and x is cycle-index, y
For the corresponding cell health state of cycle-index, σ2 2For the variance of y in the case of y=y (a, x).
Further, in this embodiment using likelihood function as P2(likelihood probability) is about ω's (actual parameter vector)
Functional relation, wherein x (cycle-index) and y (cell health state) is parameter.
S210, it is based on likelihood function and prior distribution, determines the posteriority of the actual parameter vector of each default type battery
Distribution；
In the present embodiment, in the likelihood function and prior distribution of the actual parameter vector for determining each default type battery
Afterwards, according to likelihood function and prior distribution, using Bayes' theorem, can determine the actual parameter of each default type battery to
The Posterior distrbutionp of amount are as follows:
Wherein, P3For posterior probability, ω is actual parameter vector, and x is cycle-index, and y is the corresponding battery of cycle-index
Health status, P1(ω) is the prior distribution of each default type battery actual parameter vector, P2(y | ω)==N (y | y (a,
X), σ2 2) it is the likelihood function for each presetting the actual parameter vector of type battery.
Further, in this embodiment using Posterior distrbutionp as P3(posterior probability) is about ω's (actual parameter vector)
Functional relation, wherein x (cycle-index) and y (cell health state) is parameter.
S211, corresponding estimation function at Posterior distrbutionp maximum value is obtained；
It, can be according to pole after obtaining the Posterior distrbutionp of the actual parameter vector of each default type battery in the present embodiment
Maximum-likelihood thought obtains corresponding estimation function at the Posterior distrbutionp maximum value of each default type battery, wherein estimation respectively
Function is the function of ω (actual parameter vector) about x (cycle-index) and y (cell health state).
S212, the current state parameter for extracting each default type battery is concentrated from practical health status；
Specifically, the current state parameter for extracting each default type battery can be concentrated from practical health status, currently
State parameter may include currently practical cell health state and the corresponding current cycle time of currently practical cell health state.
In the present embodiment, 1,2,3 number incremental order is preferably equal to according to cycle-index, successively concentrates and extracts from practical health status
The current state parameter of each battery in all default type batteries, to be iterated.
S213, current state parameter is substituted into corresponding current Posterior distrbutionp, next elder generation when being corrected next time
Distribution is tested, and, current state parameter is substituted into corresponding current estimation function, next parameter when being corrected next time
Estimate vector；
It specifically, can be using the currently practical cell health state in current state parameter as parameter y, currently practical electricity
Health status corresponding current cycle time in pond is updated in corresponding current Posterior distrbutionp as parameter x, will substitute into parameter y and
Posterior distrbutionp after parameter x is as next prior distribution when correcting next time；It will be currently practical in current state parameter
As parameter y, the corresponding current cycle time of currently practical cell health state is updated to pair cell health state as parameter x
In the current estimation function answered, obtained estimation function value is next parameter Estimation vector when correcting next time.
S214, it determines and corrects next time using Bayes' theorem according to next prior distribution and next parameter Estimation vector
When next Posterior distrbutionp；
According to next parameter Estimation vector, next theoretical longevity that type battery is each preset when amendment next time can be determined
Model is ordered, further according to next theoretical life model, determines next likelihood function of corresponding default type battery.This implementation procedure
Theoretical life model is identical with the determination process of likelihood function in the above-described embodiments, is not repeated herein.
It, can be fixed using Bayes again according to the likelihood function that next prior distribution and next parameter Estimation vector obtain
Reason determines next Posterior distrbutionp when correcting next time.Posteriority point in the determination process and above-described embodiment of next Posterior distrbutionp
The determination process of cloth is identical, is not repeated herein.
Next Posterior distrbutionp can be used as current Posterior distrbutionp, while successively extract current state parameter in sequence, after
It is continuous to be iterated.The implementation procedure of each iteration is identical, is not repeated herein.In the present embodiment, when practical health status is concentrated
Default type battery all state parameter iteration it is complete after, iteration of the default type battery terminates.
S215, each target component estimate vector preset in type battery last time iteration is obtained as target component
Vector；
After default type battery iteration terminates, the default type battery after acquisition iteration is in last time iteration
The target state estimator vector of generation, using the target state estimator vector as the target component vector of corresponding default type battery.
S216, according to target component vector, determine the cell health state assessment of revised each default type battery
Model；
According to target component vector, the cell health state assessment models of revised each default type battery are determined
Are as follows:
Y=(ω *, x)+ε ε~N (0, σ1 2)
Wherein, x is cycle-index, and y is the corresponding health status of cycle-index, and ω * is target component vector.Battery health
Status assessment model is the functional relation of y (cell health state) about x (cycle-index).
Further, the cell health state assessment models of the present embodiment can there are many forms of expression, such as pass through letter
The performance of number relational expression passes through curve graph performance etc..In the present embodiment, health status and circulation time are shown in order to more intuitive
The form of several relationships, the present embodiment and curve graph indicates cell health state assessment models.
Fig. 3 is a kind of schematic diagram of cell health state assessment models of the invention under dual factors effect.The present embodiment
In, preferably using temperature, driving behavior as default influence factor, obtain strong in the battery preset under influence factor effect
Health status assessment model.Referring to Fig. 3, it is low temperature+difference driving behavior battery health that a curve, which is default influence factor, in Fig. 3
Status assessment model, b curve are that default influence factor is low temperature+good driving behavior cell health state assessment models, c curve
It is room temperature+difference driving behavior cell health state assessment models for default influence factor, d curve is that default influence factor is normal
Temperature+good driving behavior cell health state assessment models.It should be noted that the present embodiment is only to default influence factor
Value volume and range of product carries out example, is not limiting upon the present invention.
S217, all cell health state assessment models are stored into preset cell health state assessment models library.
After the cell health state assessment models for determining each default type battery, all cell health states can be commented
Estimate model to store into preset cell health state assessment models library, so that when the health status of assessment mesuring battary, it can be with
From preset cell health state assessment models library, the cell health state assessment mould of corresponding default type battery is determined
Type obtains after the characteristic of battery to be assessed to be input to the cell health state assessment models of corresponding default type battery
The health status for the battery to be assessed that must be exported.
The cell health state assessment models construction method of the present embodiment according to theoretical operating parameter collection, is established each first
The theoretical life model of default type battery, then determine that each default type battery corresponds to prior distribution and likelihood function, is based on
Prior distribution and likelihood function determine each default corresponding Posterior distrbutionp of type battery, obtain the target component of Posterior distrbutionp,
Based on target component and practical health status collection, preset iterative instruction is executed, finally obtains revised each default type
The cell health state assessment models of battery.The present embodiment realize do not need the degradation to electrode material, diaphragm state,
The content of lithium ion measures in voltage, internal resistance and electrolyte, only can be to battery by the cycle-index of mesuring battary
Health status carries out online evaluation, and place to use is unrestricted, can be with real-time detection, and practicability is higher.
Fig. 4 is a kind of flow chart of cell health state appraisal procedure embodiment of the invention.As shown in figure 4, this implementation
The cell health state appraisal procedure of example can specifically include following steps:
S301, the characteristic for obtaining battery to be assessed；
In the present embodiment, the characteristic of battery to be assessed can be obtained by the state sensor of battery.Wherein feature
Data may include the type, influence factor and current cycle time of battery to be assessed.Influence factor include battery attributes, BMS,
Battery use environment, charge-discharge characteristics and driving preference.
S302, from all cell health state assessment models pre-established, it is determining with battery variety to be assessed and shadow
The target battery health state evaluation model that the factor of sound is consistent；
From cell health state assessment models library, the mesh being consistent with the type of battery to be assessed with influence factor is determined
Cell health state assessment models are marked, cell health state assessment models are assessed by the cell health state of above embodiments
Model building method building, it is not repeated herein.
S303, it is based on current cycle time and target battery health state evaluation model, determines the health of battery to be assessed
State.
The current cycle time of mesuring battary is input in target battery health state evaluation model, output knot is obtained
Fruit, the output result are the health status of battery to be assessed.
The cell health state appraisal procedure of the present embodiment is built by obtaining the characteristic of battery to be assessed from advance
In vertical all cell health state assessment models, determine that the target battery being consistent with battery variety to be assessed, influence factor is strong
Health status assessment model is based on current cycle time and target battery health state evaluation model, determines the strong of battery to be assessed
Health state realizes and does not need the degradation to electrode material, diaphragm state, voltage, lithium ion in internal resistance and electrolyte
Content measures, and only can carry out online evaluation to the health status of battery by the cycle-index of mesuring battary, and make
It is unrestricted with place, can be with real-time detection, practicability is higher.
Fig. 5 is a kind of structure chart of cell health state assessment models construction device embodiment one of the invention.In order to more
Comprehensively, correspond to cell health state assessment models construction method provided in an embodiment of the present invention, present invention also provides batteries
Health state evaluation model construction device.As shown in figure 5, cell health state assessment models construction device of the invention can wrap
It includes the first acquisition module 101, establish module 102 and correction module 103；
First obtains module 101, for obtaining the theoretical operating parameter collection of each default type battery；
Module 102 is established, for establishing the theoretical service life mould of each default type battery based on theoretical operating parameter collection
Type；
First obtains module 101, is also used to obtain reality of each default type battery under default influence factor effect
Operating parameter collection；
Correction module 103, for being based on actual operation parameters collection, respectively to the theoretical service life mould of each default type battery
Type is modified, and obtains each of the lower cell health state assessment models for presetting type battery of default influence factor effect, with
After so that the characteristic by battery to be assessed is input to the cell health state assessment models of corresponding default type battery, obtain
The health status of the battery to be assessed of output.
The cell health state assessment models construction device of the present embodiment obtains module 101 by first and obtains battery
Theoretical operating parameter collection；Based on theoretical operating parameter collection, the theoretical service life mould that module 102 establishes each default type battery is established
Type；First acquisition module 101 obtains actual operation parameters collection of each default type battery under default influence factor effect；It repairs
Positive module 103 is based on actual operation parameters collection, is modified, obtains to the theoretical life model of each default type battery respectively
The cell health state assessment models of default type battery each of under default influence factor effect, so that by battery to be assessed
After characteristic is input to the cell health state assessment models of corresponding default type battery, the battery to be assessed of output is obtained
Health status, realize do not need the degradation to electrode material, diaphragm state, voltage, in internal resistance and electrolyte lithium from
The content of son measures, and only can carry out online evaluation to the health status of battery by the cycle-index of mesuring battary, and
And place to use is unrestricted, and it can be with real-time detection, practicability is higher.
About the device in above-described embodiment, wherein modules execute the concrete mode of operation in related this method
Embodiment in be described in detail, no detailed explanation will be given here.
Fig. 6 is a kind of structure chart of cell health state assessment models construction device embodiment two of the invention.This implementation
It is further right in further detail on the basis of the cell health state assessment models construction device of example is the embodiment described in Fig. 5
Technical solution of the present invention is described.
Specifically, theoretical operating parameter collection includes that all batteries in each default type battery recycle corresponding reason every time
By health status collection；
As shown in fig. 6, the present embodiment establishes module 102, it is specifically used for being determined each pre- according to theoretical health status collection
If the parameter Estimation vector of type battery；According to parameter Estimation vector, the theoretical life model of each default type battery is determined.
Further, actual operation parameters collection include all batteries in each default type battery recycle every time it is corresponding
The practical health status collection of practical health status composition；
The correction module 103 of the present embodiment is specifically used for determining each default type battery according to theoretical health status collection
Corresponding theoretical parameter vector set；
Based on theoretical parameter vector set, the prior distribution of the actual parameter vector of each default type battery is determined；
According to theoretical life model, the likelihood function of the actual parameter vector of each default type battery is determined；
Based on likelihood function and prior distribution, the Posterior distrbutionp of the actual parameter vector of each default type battery is determined；
Obtain corresponding estimation function at Posterior distrbutionp maximum value；
Based on Posterior distrbutionp, estimation function and practical health status collection, preset iterative instruction is executed, is obtained each default
The target component vector of type battery；
According to target component vector, the cell health state assessment models of revised each default type battery are determined；
Further, the target component includes corresponding at the Posterior distrbutionp result and Posterior distrbutionp maximum value of Posterior distrbutionp
Parameter vector posterior estimate；
Correction module 103 is specifically also used to concentrate the current shape for extracting each default type battery from practical health status
State parameter, current state parameter includes currently practical cell health state and currently practical cell health state is corresponding currently follows
Ring number；
Current state parameter is substituted into corresponding current Posterior distrbutionp, next priori when being corrected next time point
Cloth, and, current state parameter is substituted into corresponding estimation function, next parameter Estimation when being corrected next time to
Amount；
It is determined when correcting next time according to next prior distribution and next parameter Estimation vector using Bayes' theorem
Next Posterior distrbutionp；
The target component estimate vector in each default type battery last time iteration is obtained as target component vector；
Further, the correction module 103 is specifically also used to concentrate the every of each battery to theoretical health status respectively
The corresponding health status of secondary circulation is fitted, and obtains the theoretical fitting function of each battery in each default type battery；
The coefficient of each theoretical fitting function is respectively combined as theoretical parameter vector；
By the theoretical parameter of each default type battery of all theoretical parameter vectors of each default type battery composition to
Quantity set；
Further, the cell health state assessment models construction device of the present embodiment can also include memory module 104；
Memory module 104 is commented for storing all cell health state assessment models to preset cell health state
Estimate in model library.
The cell health state assessment models construction device of the present embodiment initially sets up module 102 according to theoretical operating parameter
Collection, establishes the theoretical life model of each default type battery, and correction module 103 determines that each default type battery is corresponding first again
Distribution and likelihood function are tested, prior distribution and likelihood function are based on, each default corresponding Posterior distrbutionp of type battery is determined, obtains
The target component of Posterior distrbutionp is taken, based on target component and practical health status collection, preset iterative instruction is executed, finally obtains
The cell health state assessment models of revised each default type battery.The present embodiment, which realizes, not to be needed to electrode material
Degradation, diaphragm state, voltage, the content of lithium ion measures in internal resistance and electrolyte, only pass through mesuring battary
Cycle-index can carry out online evaluation to the health status of battery, and place to use is unrestricted, can be real with real-time detection
It is higher with property.
About the device in above-described embodiment, wherein modules execute the concrete mode of operation in related this method
Embodiment in be described in detail, no detailed explanation will be given here.
Fig. 7 is a kind of structure chart of cell health state assessment Installation practice of the invention.In order to more comprehensively, correspond to
Cell health state appraisal procedure provided in an embodiment of the present invention, present invention also provides cell health states to assess device.Such as
Shown in Fig. 7, cell health state assessment device of the invention may include the second acquisition module 105 and determining module 106；
Second obtains module 105, for obtaining the characteristic of battery to be assessed；Characteristic includes battery to be assessed
Type, influence factor and current cycle time；
Determining module 106, for determining and electricity to be assessed from all cell health state assessment models pre-established
The target battery health state evaluation model that pond type, influence factor are consistent；Cell health state assessment models pass through above real
Apply the building of cell health state assessment models construction method described in example；
Determining module 106 is also used to determine to be evaluated based on current cycle time and target battery health state evaluation model
Estimate the health status of battery.
The cell health state of the present embodiment assesses device, and the spy of battery to be assessed is obtained by the second acquisition module 105
Data are levied, determining module 106 is from all cell health state assessment models pre-established, determining and battery kind to be assessed
The target battery health state evaluation model that class, influence factor are consistent is based on current cycle time and target battery health status
Assessment models determine the health status of battery to be assessed, realize do not need the degradation to electrode material, diaphragm state,
The content of lithium ion measures in voltage, internal resistance and electrolyte, only can be to battery by the cycle-index of mesuring battary
Health status carries out online evaluation, and place to use is unrestricted, can be with real-time detection, and practicability is higher.
About the device in above-described embodiment, wherein modules execute the concrete mode of operation in related this method
Embodiment in be described in detail, no detailed explanation will be given here.
It is understood that same or similar part can mutually refer in the various embodiments described above, in some embodiments
Unspecified content may refer to the same or similar content in other embodiments.
It should be noted that in the description of the present invention, term " first ", " second " etc. are used for description purposes only, without
It can be interpreted as indication or suggestion relative importance.In addition, in the description of the present invention, unless otherwise indicated, the meaning of " multiple "
Refer at least two.
Any process described otherwise above or method description are construed as in flow chart or herein, and expression includes
It is one or more for realizing specific logical function or process the step of executable instruction code module, segment or portion
Point, and the range of the preferred embodiment of the present invention includes other realization, wherein can not press shown or discussed suitable
Sequence, including according to related function by it is basic simultaneously in the way of or in the opposite order, Lai Zhihang function, this should be of the invention
Embodiment person of ordinary skill in the field understood.
It should be appreciated that each section of the invention can be realized with hardware, software, firmware or their combination.Above-mentioned
In embodiment, software that multiple steps or method can be executed in memory and by suitable instruction execution system with storage
Or firmware is realized.It, and in another embodiment, can be under well known in the art for example, if realized with hardware
Any one of column technology or their combination are realized: having a logic gates for realizing logic function to data-signal
Discrete logic, with suitable combinational logic gate circuit specific integrated circuit, programmable gate array (PGA), scene
Programmable gate array (FPGA) etc..
Those skilled in the art are understood that realize all or part of step that above-described embodiment method carries
It suddenly is that relevant hardware can be instructed to complete by program, the program can store in a kind of computer-readable storage medium
In matter, which when being executed, includes the steps that one or a combination set of embodiment of the method.
It, can also be in addition, each functional unit in each embodiment of the present invention can integrate in a processing module
It is that each unit physically exists alone, can also be integrated in two or more units in a module.Above-mentioned integrated mould
Block both can take the form of hardware realization, can also be realized in the form of software function module.The integrated module is such as
Fruit is realized and when sold or used as an independent product in the form of software function module, also can store in a computer
In read/write memory medium.
Storage medium mentioned above can be read-only memory, disk or CD etc..
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is included at least one embodiment or example of the invention.In the present specification, schematic expression of the above terms are not
Centainly refer to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be any
One or more embodiment or examples in can be combined in any suitable manner.
Although the embodiments of the present invention has been shown and described above, it is to be understood that above-described embodiment is example
Property, it is not considered as limiting the invention, those skilled in the art within the scope of the invention can be to above-mentioned
Embodiment is changed, modifies, replacement and variant.
Claims (10)
1. a kind of cell health state assessment models construction method characterized by comprising
Obtain the theoretical operating parameter collection of each default type battery；
Based on the theoretical operating parameter collection, the theoretical life model of each default type battery is established；
Obtain actual operation parameters collection of each default type battery under default influence factor effect；
Based on the actual operation parameters collection, the theoretical life model of each default type battery is repaired respectively
Just, the cell health state assessment models of the default type battery each of are obtained under the default influence factor effect, with
After so that the characteristic by battery to be assessed is input to the cell health state assessment models of the corresponding default type battery,
Obtain the health status of the battery to be assessed of output.
2. a kind of cell health state assessment models construction method according to claim 1, which is characterized in that the theory
Operating parameter collection includes that all unit cells in each default type battery recycle corresponding theoretical health status collection every time；
It is described to be based on the theoretical operating parameter collection, establish the theoretical life model of each default type battery, comprising:
According to the theoretical health status collection, the parameter Estimation vector of each default type battery is determined；
According to the parameter Estimation vector, the theoretical life model of each default type battery is determined.
3. a kind of cell health state assessment models construction method according to claim 2, which is characterized in that the reality
Operating parameter collection includes that all unit cells in each default type battery recycle corresponding practical health status collection every time；
It is described to be based on the actual operation parameters collection, respectively to the theoretical life model of each default type battery into
Row amendment, the cell health state for obtaining each of the lower default type battery of the default influence factor effect assess mould
Type, comprising:
According to the theoretical health status collection, the corresponding theoretical parameter vector set of each default type battery is determined；
Based on the theoretical parameter vector set, the prior distribution of the actual parameter vector of each default type battery is determined；
According to the theoretical life model, the likelihood letter of the actual parameter vector of each default type battery is determined
Number；
Based on the likelihood function and the prior distribution, the actual parameter vector of each default type battery is determined
Posterior distrbutionp；
Obtain corresponding estimation function at the Posterior distrbutionp maximum value；
Based on the Posterior distrbutionp, the estimation function and the practical health status collection, preset iterative instruction is executed, is obtained
The target component vector of each default type battery；
According to the target component vector, the cell health state assessment models of revised each default type battery are determined.
4. a kind of cell health state assessment models construction method according to claim 3, which is characterized in that described to be based on
The Posterior distrbutionp, the estimation function and the practical health status collection, execute preset iterative instruction, obtain each described
The target component vector of default type battery, comprising:
The current state parameter for extracting each default type battery, the current state parameter are concentrated from practical health status
Including currently practical cell health state and the corresponding current cycle time of the currently practical cell health state；
The current state parameter is substituted into corresponding current Posterior distrbutionp, next priori when being corrected next time point
Cloth, and, the current state parameter is substituted into corresponding current estimation function, is obtained described next when correcting next time
Parameter Estimation vector；
According to next prior distribution and next parameter Estimation vector, using Bayes' theorem, determination is described next time
Next Posterior distrbutionp when amendment；
The target component estimate vector in each default type battery last time iteration is obtained as the target component
Vector.
5. a kind of cell health state assessment models construction method according to claim 3, which is characterized in that the basis
The theory health status collection determines the corresponding theoretical parameter vector set of each default type battery, comprising:
The corresponding health status of circulation every time of each unit cells is concentrated to intend the theoretical health status respectively
It closes, obtains the theoretical fitting function of each unit cells in each default type battery；
The coefficient of each theoretical fitting function is respectively combined as theoretical parameter vector；
All theoretical parameter vectors of each default type battery are formed to the institute of each default type battery
State theoretical parameter vector set.
6. a kind of cell health state assessment models construction method according to claim 1, which is characterized in that described to obtain
Each of under the default influence factor effect after the cell health state assessment models of the default type battery, also wrap
It includes:
All cell health state assessment models are stored into preset cell health state assessment models library.
7. a kind of cell health state appraisal procedure characterized by comprising
Obtain the characteristic of battery to be assessed；The characteristic include the type of the battery to be assessed, influence factor and
Current cycle time；
From all cell health state assessment models pre-established, the determining and described battery variety to be assessed, influence factor
The target battery health state evaluation model being consistent；The cell health state assessment models pass through any one of claim 1-6
The cell health state assessment models construction method building；
Based on the current cycle time and target battery health state evaluation model, the healthy shape of the battery to be assessed is determined
State.
8. a kind of cell health state assessment models construction device characterized by comprising the first acquisition module establishes module
And correction module；
Described first obtains module, for obtaining the theoretical operating parameter collection of each default type battery；
It is described to establish module, for establishing the theoretical longevity of each default type battery based on the theoretical operating parameter collection
Order model；
Described first obtains module, is also used to obtain reality of each default type battery under default influence factor effect
Operating parameter collection；
The correction module, for being based on the actual operation parameters collection, respectively to described in each default type battery
Theoretical life model is modified, and the battery for obtaining each of the lower default type battery of the default influence factor effect is good for
Health status assessment model, so as to which the battery that the characteristic of battery to be assessed is input to the corresponding default type battery is good for
After health status assessment model, the health status of the battery to be assessed of output is obtained.
9. a kind of cell health state assessment models construction device according to claim 8, which is characterized in that the theory
Operating parameter collection includes that all unit cells in each default type battery recycle corresponding theoretical health status collection every time；
It is described to establish module, it is also used to determine the parameter of each default type battery according to the theoretical health status collection
Estimate vector；According to the parameter Estimation vector, the theoretical life model of each default type battery is determined.
10. a kind of cell health state assesses device characterized by comprising second obtains module and determining module；
Described second obtains module, for obtaining the characteristic of battery to be assessed；The characteristic includes described to be assessed
Type, influence factor and the current cycle time of battery；
The determining module, for from all cell health state assessment models pre-established, it is determining with it is described to be assessed
The target battery health state evaluation model that battery variety, influence factor are consistent；The cell health state assessment models pass through
Cell health state assessment models construction method building described in any one of claims 1-6；
The determining module is also used to determine institute based on the current cycle time and target battery health state evaluation model
State the health status of battery to be assessed.
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